Abstract: Visible-infrared cross-modality person re-identification technology has garnered wide attention for its ability to provide round-the-clock monitoring regardless of nighttime conditions. We aim to help researchers find suitable solutions by analyzing existing methods, their applicable scenarios, and the advantages and disadvantages of different algorithms. Additionally, We seek to identify current challenges and explores future directions for visible-infrared cross-modality person re-identification. We first introduce the concept of person re-identification, review its development, and highlight the significance of visible-infrared cross-modality person re-identification. Subsequently, it categorizes research methods into basic methods, auxiliary model, unsupervised methods, and video-based approaches, analyzing their applicable scenarios, advantages, disadvantages, and potential future research directions. We also discuss current evaluation metrics and existing datasets for visible-infrared cross-modality person re-identification, analyzing the strengths and weaknesses of each dataset. Finally, We discuss the future prospects in this area.